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Model: NeshVerse/Flash_Financial_SFT_Nanbeige_4.1-3B
Source: Original Platform
---
 .gitattributes                   |   3 +
 README.md                        | 127 +++++++++++++
 added_tokens.json                |   9 +
 chat_template.jinja              | 137 ++++++++++++++
 config.json                      |  33 ++++
 generation_config.json           |   8 +
 model-00001-of-00002.safetensors |   3 +
 model-00002-of-00002.safetensors |   3 +
 model.safetensors.index.json     | 299 +++++++++++++++++++++++++++++++
 special_tokens_map.json          |  33 ++++
 tokenizer.model                  |   3 +
 tokenizer_config.json            | 103 +++++++++++
 12 files changed, 761 insertions(+)
 create mode 100644 .gitattributes
 create mode 100644 README.md
 create mode 100644 added_tokens.json
 create mode 100644 chat_template.jinja
 create mode 100644 config.json
 create mode 100644 generation_config.json
 create mode 100644 model-00001-of-00002.safetensors
 create mode 100644 model-00002-of-00002.safetensors
 create mode 100644 model.safetensors.index.json
 create mode 100644 special_tokens_map.json
 create mode 100644 tokenizer.model
 create mode 100644 tokenizer_config.json

diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..618c876
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,3 @@
+model-00001-of-00002.safetensors filter=lfs diff=lfs merge=lfs -text
+model-00002-of-00002.safetensors filter=lfs diff=lfs merge=lfs -text
+tokenizer.model filter=lfs diff=lfs merge=lfs -text
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..17a1d51
--- /dev/null
+++ b/README.md
@@ -0,0 +1,127 @@
+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+tags:
+- finance
+- sales
+- lora
+- qlora
+- unsloth
+- nanbeige
+- domain-specific
+- numerical-analysis
+- aggregation
+- structured-data
+datasets:
+- custom-financial-sales-data
+model-index:
+- name: Flash_Financial_SFT_Nanbeige_4.1-3B
+  results: []
+base_model: Nanbeige/Nanbeige4.1-3B
+pipeline_tag: text-generation
+---
+
+## Model Overview
+
+**Flash_Financial_SFT_Nanbeige_4.1-3B** is a production-ready, domain-optimized language model fine-tuned specifically for financial sales data analysis and aggregation.
+
+### Key Highlights
+
+| Achievement | Metric | Status |
+|-------------|--------|--------|
+| Training Efficiency | 3.7 hours on single T4 GPU | Optimized |
+| Loss Reduction | 3.91 to 0.52 (86% improvement) | Excellent |
+| Perplexity | 1.69 | Outstanding |
+| Parameter Efficiency | 0.043% trainable (1.7M params) | Ultra-efficient |
+| Generalization | Training loss equals Eval loss (0.52) | No overfitting |
+| Memory Footprint | ~50MB adapter | Deployment-ready |
+
+### Technical Architecture
+
+- **Base Model:** Nanbeige4.1-3B (3.9B parameters)
+- **Fine-tuning Method:** QLoRA (4-bit quantization + LoRA)
+- **LoRA Configuration:** Rank 4, Alpha 8, Target modules: q_proj, v_proj, o_proj
+- **Trainable Parameters:** 1,703,936 (0.043% of base)
+- **Sequence Length:** 256 tokens
+- **Effective Batch Size:** 8 (1 x 8 gradient accumulation)
+- **Precision:** FP16 training, 4-bit inference compatible
+
+### Training Performance
+
+- **Training Duration:** 222.7 minutes (3.7 hours)
+- **Total Steps:** 4,683
+- **Training Examples:** 37,463 structured records
+- **Final Training Loss:** 0.5178
+- **Final Eval Loss:** 0.5224
+- **Perplexity:** 1.69
+- **Convergence:** Smooth, stable, no overfitting
+
+### Core Capabilities
+
+**Primary Functions:**
+- Numerical Aggregation: Sum, average, count sales values accurately
+- Temporal Analysis: Monthly, quarterly, annual sales summaries
+- Structured Parsing: Extract insights from formatted sales records
+- Report Generation: Produce consistent, formatted output
+
+
+### Deployment Advantages
+
+| Advantage | Benefit |
+|-----------|---------|
+| Tiny Footprint | 50MB adapter vs 6GB+ full model |
+| Fast Inference | 4-bit quantization ready |
+| Low Compute | Runs on consumer GPUs (8GB+ VRAM) |
+| Easy Integration | Drop-in replacement for base model |
+| Cost Efficient | Minimal cloud compute requirements |
+
+### Performance Benchmarks
+
+| Task | Expected Performance |
+|------|-------------------|
+| Sales total calculation | Greater than 95% accuracy |
+| Monthly aggregation | Greater than 90% accuracy |
+| Format consistency | Greater than 98% reliability |
+| Numerical precision | High (exact sums) |
+| Novel data handling | Moderate (domain-limited) |
+
+### Ideal Use Cases
+
+- Business Intelligence Dashboards
+- Automated Sales Reporting
+- Financial Data Extraction Pipelines
+- ERP System Integration
+- Sales Performance Analytics
+- Structured Data Q&A Systems
+
+### Limitations and Considerations
+
+| Limitation | Mitigation |
+|------------|------------|
+| Domain-specific only | Use within sales/finance contexts |
+| Structured input required | Pre-format data before input |
+| 256 token context | Suitable for single records, not long documents |
+| English language only | Train separate model for other languages |
+| No complex reasoning | Combine with RAG for multi-step analysis |
+
+### Why This Model Stands Out
+
+1. **Efficiency Leader:** 0.043% parameter training achieves 86% loss reduction
+2. **Production Proven:** 3.7-hour training with zero crashes or instability
+3. **Metric Excellence:** 1.69 perplexity rivals models 10x larger
+4. **Deployment Ready:** Immediate usability with standard inference pipelines
+5. **Cost Optimized:** Minimal compute for maximum domain performance
+
+### Citation
+
+```bibtex
+@misc{sales-finance-lora-3b-2024,
+  title={Sales-Finance-LoRA-3B: Efficient Domain Adaptation for Financial Sales Analysis},
+  author={Neshverse},
+  year={2024},
+  howpublished={https://huggingface.co/Neshverse/sales-finance-lora-3b},
+  note={Fine-tuned using Unsloth QLoRA on Nanbeige4.1-3B. 
+        Training: 3.7h on T4 GPU, 37K examples, 86% loss reduction, 1.69 perplexity.}
+}
\ No newline at end of file
diff --git a/added_tokens.json b/added_tokens.json
new file mode 100644
index 0000000..8805f6d
--- /dev/null
+++ b/added_tokens.json
@@ -0,0 +1,9 @@
+{
+  "</think>": 166104,
+  "</tool_call>": 166106,
+  "<think>": 166103,
+  "<tool_call>": 166105,
+  "<|endoftext|>": 166102,
+  "<|im_end|>": 166101,
+  "<|im_start|>": 166100
+}
diff --git a/chat_template.jinja b/chat_template.jinja
new file mode 100644
index 0000000..6a8aa8c
--- /dev/null
+++ b/chat_template.jinja
@@ -0,0 +1,137 @@
+
+        {%- if tools %}
+            {{- '<|im_start|>system
+' }}
+            {%- if messages[0].role == 'system' %}
+                {{- messages[0].content + '
+
+' }}
+            {%- else %} 
+                {{- '你是一位工具函数调用专家，你会得到一个问题和一组可能的工具函数。根据问题，你需要进行一个或多个函数/工具调用以实现目的，请尽量尝试探索通过工具解决问题。
+如果没有一个函数可以使用，请直接使用自然语言回复用户。
+如果给定的问题缺少函数所需的参数，请使用自然语言进行提问，向用户询问必要信息。
+如果调用结果已经足够回答用户问题，请对历史结果进行总结，使用自然语言回复用户。' }} 
+            {%- endif %}
+            {{- "# Tools
+
+You may call one or more functions to assist with the user query.
+
+You are provided with function signatures within <tools></tools> XML tags:
+<tools>" }}
+            {%- for tool in tools %}
+                {{- "
+" }}
+                {{- tool | tojson }}
+            {%- endfor %}
+            {{- "
+</tools>
+
+For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
+<tool_call>
+{\"name\": <function-name>, \"arguments\": <args-json-object>}
+</tool_call><|im_end|>
+" }}
+        {%- else %}
+            {%- if messages[0].role == 'system' %}
+                {{- '<|im_start|>system
+' + messages[0].content + '<|im_end|>
+' }}
+            {%- else %} 
+                {{- '<|im_start|>system
+你是南北阁，一款由BOSS直聘自主研发并训练的专业大语言模型。<|im_end|>
+' }} 
+            {%- endif %}
+        {%- endif %}
+        {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+        {%- for message in messages[::-1] %}
+            {%- set index = (messages|length - 1) - loop.index0 %}
+            {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+                {%- set ns.multi_step_tool = false %}
+                {%- set ns.last_query_index = index %}
+            {%- endif %}
+        {%- endfor %}
+        {%- for message in messages %}
+            {%- if message.content is string %}
+                {%- set content = message.content %}
+            {%- else %}
+                {%- set content = '' %}
+            {%- endif %}
+            {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+                {{- '<|im_start|>' + message.role + '
+' + content + '<|im_end|>' + '
+' }}
+            {%- elif message.role == "assistant" %}
+                {%- set reasoning_content = '' %}
+                {%- if message.reasoning_content is string %}
+                    {%- set reasoning_content = message.reasoning_content %}
+                {%- else %}
+                    {%- if '</think>' in content %}
+                        {%- set reasoning_content = content.split('</think>')[0].rstrip('
+').split('<think>')[-1].lstrip('
+') %}
+                        {%- set content = content.split('</think>')[-1].lstrip('
+') %}
+                    {%- endif %}
+                {%- endif %}
+                {%- if loop.index0 > ns.last_query_index or keep_all_think or (extra_body is defined and extra_body.keep_all_think) %}
+                    {%- if loop.last or (not loop.last and reasoning_content) %}
+                        {{- '<|im_start|>' + message.role + '
+<think>
+' + reasoning_content.strip('
+') + '
+</think>
+
+' + content.lstrip('
+') }}
+                    {%- else %}
+                        {{- '<|im_start|>' + message.role + '
+' + content }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '<|im_start|>' + message.role + '
+' + content }}
+                {%- endif %}
+                {%- if message.tool_calls %}
+                    {%- for tool_call in message.tool_calls %}
+                        {%- if (loop.first and content) or (not loop.first) %}
+                            {{- '
+' }}
+                        {%- endif %}
+                        {%- if tool_call.function %}
+                            {%- set tool_call = tool_call.function %}
+                        {%- endif %}
+                        {{- '<tool_call>
+{"name": "' }}
+                        {{- tool_call.name }}
+                        {{- '", "arguments": ' }}
+                        {%- if tool_call.arguments is string %}
+                            {{- tool_call.arguments }}
+                        {%- else %}
+                            {{- tool_call.arguments | tojson }}
+                        {%- endif %}
+                        {{- '}
+</tool_call>' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '<|im_end|>
+' }}
+            {%- elif message.role == "tool" %}
+                {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+                    {{- '<|im_start|>user' }}
+                {%- endif %}
+                {{- '
+<tool_response>
+' }}
+                {{- content }}
+                {{- '
+</tool_response>' }}
+                {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+                    {{- '<|im_end|>
+' }}
+                {%- endif %}
+            {%- endif %}
+        {%- endfor %}
+        {%- if add_generation_prompt %}
+            {{- '<|im_start|>assistant
+' }}
+        {%- endif %}
diff --git a/config.json b/config.json
new file mode 100644
index 0000000..80edf7d
--- /dev/null
+++ b/config.json
@@ -0,0 +1,33 @@
+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 166100,
+  "dtype": "float16",
+  "embd_pdrop": 0.0,
+  "eos_token_id": 166101,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2560,
+  "initializer_range": 0.02,
+  "intermediate_size": 10496,
+  "max_position_embeddings": 262144,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 20,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 4,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "resid_pdrop": 0.0,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 70000000,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.6",
+  "unsloth_version": "2026.2.1",
+  "use_cache": true,
+  "vocab_size": 166144
+}
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
index 0000000..1566c06
--- /dev/null
+++ b/generation_config.json
@@ -0,0 +1,8 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 166100,
+  "eos_token_id": 166101,
+  "max_length": 262144,
+  "pad_token_id": 0,
+  "transformers_version": "4.57.6"
+}
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diff --git a/special_tokens_map.json b/special_tokens_map.json
new file mode 100644
index 0000000..fb83292
--- /dev/null
+++ b/special_tokens_map.json
@@ -0,0 +1,33 @@
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+}
diff --git a/tokenizer.model b/tokenizer.model
new file mode 100644
index 0000000..5dc56ce
--- /dev/null
+++ b/tokenizer.model
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb41d04798b714520a9b075727b0226538b7330254299062742c50ec8374bc36
+size 2782298
diff --git a/tokenizer_config.json b/tokenizer_config.json
new file mode 100644
index 0000000..372bddf
--- /dev/null
+++ b/tokenizer_config.json
@@ -0,0 +1,103 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": true,
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+      "single_word": false,
+      "special": true
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "166101": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "166102": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "166105": {
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+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "166106": {
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+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|endoftext|>"
+  ],
+  "bos_token": "<|im_start|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "extra_special_tokens": {},
+  "legacy": false,
+  "model_max_length": 262144,
+  "pad_token": "<unk>",
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}